همایش ملی بیوانفورماتیک ایران

صفحه اصلی / 4th international edition and 13th Iranian Conference on Bioinformatics

A computational approach to identify the biomarker based on the RNA sequencing data analysis for Alzheimer’s disease

نویسندگان :

Atena Vaghf¹ Shahram Tahmasebian² Nayereh Abdali³

1- Student Research Committee, Shahrekord University of Medical Sciences, Shahrekord, Iran 2- Department of Medical Biotechnology, School of Advanced Technologies, Shahrekord University of Medical Sciences, Shahrekord, Iran 3- Student Research Committee, Shahrekord University of Medical Sciences, Shahrekord, Iran

کلمات کلیدی :

Alzheimer’s disease،RNA sequencing،miR-9-5p،GABRB2

چکیده :

Introduction: Alzheimer’s disease (AD) is a progressive neurodegenerative disease. AD affects at least 27 million people and is associated with a high impact on the life of the patient’s family and a huge financial cost to society. RNA sequencing (RNA-seq) is one effective approach to finding the heterogeneous gene expressions of diseases that helps discover new functional genes as prognostic biomarkers. Besides, It is well-known that microRNA (miRNAs) biomarkers have emerged as a powerful screening tool, as they are highly expressed in CRC patients and easily detectable in several biological samples. The bioinformatics method is cost-effective and time-saving when studying the role of miRNAs-mRNA. Therefore, in this study computational models were used to identify AD-related biomarker by RNA-seq analysis. Methods: The RNA sequencing of 40 AD samples with 8 healthy control tissue from the occipital lobe under the accession code GSE203206 were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/). The differentially expressed genes (DEGs) between AD and normal tissues were obtained by using GEO2R. The 1000 top up regulated genes were imported into the STRING (version 12.0, http://string-db.org) database to identify the interactive association between the proteins. Then, the all interactions with a significant combined score >0.4 were selected for further analysis. The appropriate gene with the highest degrees of connectivity were selected as hub genes. The targetSacn database is a specialized collection of microRNA-mRNA targeting relationships. These databases were used to obtain hub gene-associated miRNA. Results: This study identified 4150 genes with |log2FC|>0.5 and P-value <0.01 as DEGs: 1279 upregulated and 2871 downregulated genes. γ-aminobutyric acid receptors β2 subunit gene (GABRB2) was identified as one of the best hub gene in STRING which hsa-miR-9-5p can suppressed the GABRB2 expression in AD. GABRB2 has a pivotal role in the central nervous system. Several studies also reported alterations in GABA levels, typically a reduction in total neurotransmitter concentration in several regions of the post-mortem AD brain. As recorded, miR-9-5p is found to be downregulated in the brain of the AD patients. Overexpression of miR-9-5p modulates neuroinflammation in the central nervous system. Of note, this bioinformatic results confirmed that targeting GABRB2 is an important mechanism of AD function improving by miR-9-5p in AD. Moreover, TargetScan indicating that the seed region of miR-9-5p contains 2 complementary sites within position 4645-4652 and 4726-4732 of GABRB2 3' UTR. Conclusion: Taken together, our findings from RNA sequencing analysis provide the first clues regarding the role of miR-9-5p as a modulator the progression of AD by inhibiting GABRB2 translation. The results also provide valuable insights into the regulation of miR-9-5p and GABRB2 for future research and therapeutic development. These can be used as a specific diagnostic index and therapeutic target for patients with AD.